This course offers you practical training in machine learning, using the R program. At the end of the course you will know how to use the most widespread machine learning techniques to make accurate predictions and get valuable insights from your data.
All the machine learning procedures are explained live, in detail, on real life data sets. So you will advance fast and be able to apply your knowledge immediately no need for painful trial–and–error to figure out how to implement this or that technique in R. Within a short time you can have a solid expertise in machine learning.
Machine learning skills are very valuable if you intent to secure a job like data analyst, data scientist, researcher or even software engineer. So it may be the right time for you to enroll in this course and start building your machine learning competences today!
Let s see what you are going to learn here.
First of all, we are going to discuss some essential concepts that you must absolutely know before performing machine learning. So we ll talk about supervised and unsupervised machine learning techniques, about the distinctions between prediction and inference, about the regression and classification models and, above all, about the bias–variance trade–off, a crucial issue in machine learning.
Instructor Details
Courses : 2
Specification: Applied Machine Learning in R
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20 reviews for Applied Machine Learning in R
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Price | $11.99 |
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Provider | |
Duration | 8 hours |
Year | 2020 |
Level | All |
Language | English |
Certificate | Yes |
Quizzes | No |
$94.99 $11.99
Meghana Rao –
This course is like a ready reckoner for revising core concepts in a short duration of time. The concepts got cleared in one go. I would recommend this course to everyone who wants a crisp and a quick walk through of all the essentials in Machine Learning. Thank you Sir for creating this course!
Jose Ramon Villatuya –
The course gets you to the meat of the matter fast. Further details can be researched after you’ve learned the fundamentals. I believe some knowledge of statistical inference will be helpful to allow a more quicker consumption of the topics. This course can also serve as a quick revision for those with some background in ML already. In my opinion, Bogdan Anastasiei was able to structure the course in a manner that minimizes confusion (and maybe frustration) for the initiated beginning ML learner.
Cristian Dinu –
Best R Machine learning course I attended until today. Thank you Bogdan !
Sue McLeod –
So far the course is about revising concepts and ideas which is exactly what I need.
Karunakar Chinnabathini –
I am expecting more of a probabilistic view of ML algorithms.
Amit Kumar Das –
Splendid explanation…
Pawan Solanki –
yes
Matt Milligan –
Good explanations. Easy pace.
Roger Holeywell –
Clear explanations. Keeping it simple to start with. Very succinct lectures. Well annotated R code. Nice that PPT slides and R scripts are downloadable.
Patrick.Dolinger –
The instructor is quite knowledgeable and it shows through in his examples.
Riyan –
just reading what is in ppt
Viswanadhareddy N –
it is so good .
Nithishsaran H –
Nice
Divyakant Thakarshibhai Meva –
Really good experience
Jyoti singh –
Yes
C.Padmavathy –
yes
Amit Khemchandani –
TUTOR IS VERY GOOD AND CONTENT QUALITY EXCELLENT
Eman Toraih –
Easy way of explanation, organized, systematic flow of ideas.
Mohamed Yehia Abdellatif Mohamed Ghanem –
Clear and to the point.
Rita Olla –
In general is ok, no assistance tho in case of problems that I figure out by my self